Surface defect detecting method and surface defect detecting apparatus

ABSTRACT

A detecting method of optically detecting a surface defect of a moving steel material includes an irradiation step of irradiating an examination target part with illumination light beams from different directions by two or more distinguishable light sources whose light emission durations are set based on at least an allowable positional displacement of an image, the two or more distinguishable light sources repeatedly emitting light such that their light emission timings thereof do not overlap each other; and a detection step of obtaining images by reflected light beams of the respective illumination light beams and detecting a surface defect in the examination target part by executing subtraction processing between the obtained images.

TECHNICAL FIELD

This disclosure relates to a surface defect detecting method and asurface defect detecting apparatus that optically detects a surfacedefect of a steel material.

BACKGROUND

In recent years, in manufacturing processes of steel products, in termsof improving yield through prevention of mass incompatibility, detectionof surface defects of hot or cold steel materials has been demanded.Steel materials referred to herein mean: steel products including steelsheets and shaped steel such as seamless steel pipes, welded steelpipes, hot rolled steel sheets, cold rolled steel sheets, and thickplates; and semimanufactures such as slabs produced when these steelproducts are manufactured. Thus, a method has been proposed as a methodof detecting a surface defect of a steel material, the method in which:a billet in a process of manufacturing a seamless steel pipe isirradiated with light; reflected light is received therefrom; andpresence or absence of a surface defect is determined according to lightquantity of the reflected light (see Japanese Patent ApplicationLaid-open No. 11-037949). Further, a method has also been proposed inwhich: visible light beams of plural wavelength regions, which do nothave mutual influence with emitted light radiated from a hot steelmaterial and do not influence each other, are emitted from diagonaldirections symmetrical to each other about a normal line of a surface ofthe hot steel material; an image by combined reflected light beams andimages due to the individual reflected light beams are obtained in thenormal direction of the surface of the hot steel material; and a surfacedefect of the hot steel material is detected from a combination of theseimages (see Japanese Patent Application Laid-open No. 59-052735).

According to the method described in JP '949, since reflectivity of aharmless pattern or scale is different from reflectivity of a base steelportion, the sound harmless pattern or scale may be erroneously detectedas a surface defect. Therefore, in the method described in JP '949, byutilizing the fact that the shape of the defect is linear, the defectand the scale are distinguished from each other. However, surfacedefects on a steel material not only have linear shapes, but alsovarious shapes such as circular shapes. Therefore, the method describedin JP '949 is difficult to be applied to detection processing for asurface defect of a steel material. In the method described in JP '735,since there are a vast variety of defects, scale, harmless patterns andthe like, scale or a harmless pattern is difficult to be distinguishedfrom a surface defect just by a simple combination of images. Further,realistically, detection logic corresponding to the vast number ofcombinations of images is difficult to be constructed.

It could therefore be helpful to provide a surface defect detectingmethod and a surface defect detecting apparatus that enable scale or aharmless pattern to be accurately distinguished from a surface defect.

SUMMARY

Our surface defect detecting method of optically detecting a surfacedefect of a steel material includes: an irradiation step of irradiatingan examination target part with illumination light beams from differentdirections by using two or more distinguishable light sources; and adetection step of obtaining images by reflected light beams of therespective illumination light beams and detecting a surface defect inthe examination target part by executing subtraction processing betweenthe obtained images.

The irradiation step includes a step of performing the irradiation withthe illumination light beams by causing two or more flash light sourcesto repeatedly emit light such that light emission timings thereof do notoverlap each other.

The irradiation step includes a step of simultaneously emittingillumination light beams of two or more light sources having wavelengthregions not overlapping one another, and the detection step includes astep of obtaining images by reflected light beams of the respectiveillumination light beams by separating, by use of filters that transmitlight beams having wavelengths that are the same as wavelengths of theillumination light beams, the reflected light beams of the respectiveillumination light beams that have been mixed with one another.

The irradiation step includes a step of simultaneously performingirradiation with illumination light beams of two light sources havinglinear polarization characteristics that are orthogonal to each other;and the detection step includes a step of obtaining images by reflectedlight beams of the respective illumination light beams by separating, byuse of two polarization plates having linear polarizationcharacteristics orthogonal to each other, the reflected light beams ofthe respective illumination light beams having been mixed with eachother.

An angle of incidence of the illumination light beams of the respectivelight sources with respect to the examination target part is in a rangeof not smaller than 25° and not larger than 55°.

The detection step includes a step of adjusting, by using any of a halfmirror, a beam splitter, and a prism, optical axes of plural imagingdevices, which obtain images by reflected light beams of the respectiveillumination light beams, to be coaxial with one another.

The detection step includes a first determination step of extracting abright portion and a dark portion of an image obtained by the executionof subtraction processing between the obtained images, and determiningpresence or absence of a concavo-convex surface defect from a positionalrelation between the extracted bright portion and dark portion andirradiation directions of the illumination light beams.

The first determination step includes a step of executing expansionprocessing with respect to images of the bright portion and the darkportion, and calculating a positional relation between the brightportion and the dark portion by extraction of an overlapping portionbetween the images of the bright portion and dark portion that have beensubjected to the expansion processing.

The first determination step includes a step of executing binarizationprocessing and labeling processing with respect to images of the brightportion and the dark portion, and calculating a positional relationbetween the bright portion and the dark portion by comparing positionsof the centers of gravity of the images that have been subjected to thelabeling processing.

The first determination step includes a step of calculating a positionalrelation between a bright portion and a dark portion by emphasizing thebright portion and the dark portion through filtering processing ofimages of the bright portion and dark portion.

The first determination step includes a step of: calculating, as afeature amount, at least one of a luminance ratio, an area ratio, and acircularity of the bright portion and dark portion, from a combinationof the bright portion and the dark portion obtained by the calculationof the positional relation between the bright portion and dark portion;and determining, based on the calculated feature amount, presence orabsence of a concavo-convex surface defect.

The detection step includes a second determination step of obtainingimages by reflected light beams of the respective illumination lightbeams, extracting a bright portion and a dark portion of an imageobtained by executing subtraction processing between the obtainedimages, calculating a shape feature amount that becomes an index ofelongatedness of the extracted bright portion and dark portion, anddetermining, based on the calculated feature amount, presence or absenceof an elongated defect.

The second determination step includes a step of calculating, as theshape feature amount, at least one of: a major axis-minor axis ratioaccording to elliptic approximation; a maximum Feret's diameter; acircularity; and a convex polygon filling rate.

The second determination step includes a step of determining thepresence or absence of an elongated defect, based on, in addition to theshape feature amount, a direction of the bright portion and darkportion.

The second determination step includes a step of determining a directionof the bright portion and dark portion by using any of: a majoraxis-minor axis ratio according to elliptic approximation; a maximumFeret's diameter; and a linear filter.

Our surface defect detecting apparatus optically detects a surfacedefect of a steel material, and includes: an irradiation unit configuredto irradiate an examination target part with illumination light beamsfrom different directions by using two or more distinguishable lightsources; and a detection unit configured to obtain images by reflectedlight beams of the respective illumination light beams and to detect asurface defect in the examination target part by executing subtractionprocessing between the obtained images.

The surface defect detecting apparatus optically detects a surfacedefect of a steel material, and includes: an irradiation unit configuredto irradiate an examination target part with illumination light beamsfrom different directions by using two or more distinguishable lightsources; and a determination unit configured to obtain images byreflected light beams of the respective illumination light beams, toextract a bright portion and a dark portion of an image obtained byexecuting subtraction processing between the obtained images, and todetermine presence or absence of a concavo-convex surface defect from apositional relation between the extracted bright portion and darkportion and irradiation directions of the illumination light beams.

The surface defect detecting apparatus optically detects a surfacedefect of a steel material, and includes: an irradiation unit configuredto irradiate an examination target part with illumination light beamsfrom different directions by using two or more distinguishable lightsources; and a determination unit configured to obtain images byreflected light beams of the respective illumination light beams, toextract a bright portion and a dark portion of an image obtained byexecuting subtraction processing between the obtained images, to obtaina shape feature amount that becomes an index of elongatedness of theextracted bright portion and dark portion, and to determine, based onthe calculated feature amount, presence or absence of an elongateddefect.

By a surface defect detecting method and a surface defect detectingapparatus, scale or a harmless pattern is able to be accuratelydistinguished from a surface defect.

We provide a detecting method of optically detecting a surface defect ofa moving steel material, the method comprising an irradiation step ofirradiating an examination target part with illumination light beamsfrom different directions by two or more distinguishable light sourceswhose light emission durations are set based on at least an allowablepositional displacement of an image, the two or more distinguishablelight sources repeatedly emitting light such that their light emissiontimings thereof do not overlap each other; and a detection step ofobtaining images by reflected light beams of the respective illuminationlight beams and detecting a surface defect in the examination targetpart by executing subtraction processing between the obtained images.

We further provide a surface defect detecting apparatus that opticallydetects a surface defect of a moving steel material, the surface defectdetecting apparatus comprising an irradiation unit configured toirradiate an examination target pat with illumination light beams fromdifferent directions by two or more distinguishable light sources whoselight emission durations are set based on at least an allowablepositional displacement of an image, the two or more distinguishablelight sources repeatedly emit light such that their light emissiontimings do not overlap each other; and a detection unit configured toobtain images by reflected light beams of the respective illuminationlight beams and detect a surface defect in the examination target partby executing subtraction processing between the obtained images.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating a configuration of a surfacedefect detecting apparatus according to a first structure.

FIG. 2 is a schematic diagram illustrating a configuration of a modifiedexample of area sensors illustrated in FIG. 1.

FIG. 3 is a timing chart illustrating driving timing of light sourcesand the area sensors illustrated in FIG. 1.

FIG. 4 is a diagram illustrating an example of: two two-dimensionalimages capturing a surface defect, and scale and a harmless pattern; anda subtraction image thereof.

FIG. 5 is a schematic diagram illustrating a configuration of anapparatus used in an experiment to investigate the relationship betweenangle of incidence of an illumination light and reflectivity of a soundportion (base steel portion).

FIG. 6 is a diagram illustrating the relationship between angle ofincidence of a laser and light quantity received by a power meter.

FIG. 7 is a schematic diagram for explanation of surface defectdetection processing according to a second structure.

FIG. 8 is a schematic diagram for explanation of surface defectdetection processing according to a third structure.

FIG. 9 is a schematic diagram illustrating a configuration of anapparatus used in an example.

FIG. 10 is a diagram illustrating results of surface defect detectionprocessing of the example.

FIG. 11 is a diagram illustrating results of surface defect detectionprocessing for a portion where scale has been generated.

FIG. 12 is a schematic diagram illustrating a configuration of amodified example of the surface defect detecting apparatus according tothe first structure.

FIG. 13 is a schematic diagram illustrating a configuration of anothermodified example of the surface defect detecting apparatus according tothe first structure.

FIGS. 14A and B are diagrams illustrating shade and shadow when light isemitted from one direction when surface shapes of parts to be examinedare concave and convex.

FIG. 15 is a diagram illustrating an example of a subtraction image of aconcave shaped surface defect.

FIG. 16 is a flow chart illustrating a flow of a method of calculating apositional relation between a bright portion and a dark portion byutilization of expansion processing.

FIGS. 17A and B are diagrams illustrating the subtraction image and aone-dimensional profile of a brightness pattern.

FIGS. 18A and B are diagrams illustrating an example of atwo-dimensional image and a one-dimensional profile, of a filter.

FIGS. 19A and B are diagrams illustrating an example of a subtractionimage having been subjected to filtering using the filter illustrated inFIGS. 18A and B and a one-dimensional profile thereof.

FIG. 20 is a schematic diagram illustrating a modified example ofarrangement positions of light sources.

FIGS. 21A, B and C are schematic diagrams illustrating brightnesspatterns obtained by the arrangement positions of the light sourcesillustrated in FIG. 20.

FIG. 22 is a diagram illustrating results of surface defect detectionprocessing of an example.

FIG. 23 is a diagram illustrating an example of a linear elongateddefect where a brightness pattern of reflected light is not formed.

FIG. 24 is a flow chart illustrating a flow of detection processing foran elongated defect according to one method.

FIGS. 25A, B and C are diagrams for explanation of an example of shapefeature amounts of surface defects.

FIG. 26 is a diagram illustrating results of surface defect detectionprocessing of an example.

REFERENCE SIGNS LIST

1 SURFACE DEFECT DETECTING APPARATUS

2 a, 2 b LIGHT SOURCE

3 FUNCTION GENERATOR

4 a, 4 b AREA SENSOR

5 IMAGE PROCESSING DEVICE

6 MONITOR

L ILLUMINATION LIGHT BEAM

P STEEL PIPE

DETAILED DESCRIPTION

Hereinafter, by referring to the drawings, configurations and operationof surface defect detecting apparatuses according to first to thirdstructures will be described.

First Structure

By referring to FIG. 1 to FIG. 13, a configuration and operation of asurface defect detecting apparatus according to a first structure willbe described.

Configuration of Surface Defect Detecting Apparatus

FIG. 1 is a schematic diagram illustrating the configuration of thesurface defect detecting apparatus according to the first structure. Asillustrated in FIG. 1, a surface defect detecting apparatus 1 is anapparatus that detects a surface defect of a steel pipe P, which isconveyed in a direction of an arrow illustrated in the figure, iscylindrically shaped, and the surface defect detecting apparatus 1includes, as main components thereof, light sources 2 a and 2 b, afunction generator 3, area sensors 4 a and 4 b, an image processingdevice 5, and a monitor 6.

The light sources 2 a and 2 b irradiate the same examination target parton a surface of the steel pipe P with distinguishable illumination lightbeams L, according to trigger signals from the function generator 3. Thelight sources 2 a and 2 b are desirably arranged symmetrically about theexamination target part. Therefore, the light sources 2 a and 2 b arearranged such that the light sources 2 a and 2 b are displaced from anormal vector of the surface of the steel pipe P by the same angle, andthat irradiation direction vectors of the illumination light beams L andthe normal vector of the surface of the steel pipe P are on the sameplane. The sameness of their angles of incidence mentioned herein aimsto make the optical conditions as equal as possible to each other whenthe differently directed light sources are distinguished from eachother, and to largely reduce a signal of a sound portion including scaleand a harmless pattern by subtraction processing. Further, a signal of asound portion largely depends on characteristics of a surface of atarget, and the sameness is difficult to be unconditionally guaranteedby a certain angle. Therefore, when the angles are 25° to 55°, even ifthe angles are a little different from each other, as long as a signalof a sound part is able to be reduced by subtraction processing, theangles will be expressed as being the same. In this structure, thenumber of light sources is two, but as long as the light sources aredistinguishable from one another, the number of light sources may bethree or more. Distinguishable light sources mentioned herein refer tolight sources for which a reflected light quantity is able to be foundseparately for each of the light sources with respect to reflected lightbeams obtained from a target.

The area sensors 4 a and 4 b capture two-dimensional images by reflectedlight beams of the illumination light beams L emitted from the lightsources 2 a and 2 b according to trigger signals from the functiongenerator 3. The area sensors 4 a and 4 b input data of the capturedtwo-dimensional images to the image processing device 5. The areasensors 4 a and 4 b are desirably arranged on normal vectors of anexamination target part as much as possible in a state where theirrespective imaging fields of view have been secured.

To solve a positioning problem, the area sensors 4 a and 4 b are made asclose as possible to each other, and their optical axes are made asparallel as possible to each other. Further, as illustrated in FIG. 2,the optical axes of the area sensors 4 a and 4 b may be adjusted to becoaxial by use of any of a half mirror 10, a beam splitter, and a prism.Thereby, a later described subtraction image is able to be obtainedaccurately.

The image processing device 5 is a device that detects a surface defectin an examination target part, by executing later described subtractionprocessing between two two-dimensional images input from the areasensors 4 a and 4 b. The image processing device 5 outputs the twodimensional images input from the area sensors 4 a and 4 b andinformation related to a result of the surface defect detection to themonitor 6.

By executing surface defect detection processing described below, thesurface defect detecting apparatus 1 configured as described abovedistinguishes scale or a harmless pattern from a surface defect in anexamination target part. A surface defect mentioned herein refers to aconcavo-convex defect. Further, scale or a harmless pattern means aportion having a surface film or surface characteristics with opticalproperties different from those of a base steel portion of a thicknessof about several μm to several tens of μm, and is a portion that becomesa cause of noise in the surface defect detection processing.Hereinafter, surface defect detection processing according to first tothird examples will be described.

First Example

First, by referring to FIG. 3 to FIG. 6, surface defect detectionprocessing according to a first example will be described.

FIG. 3 is a timing chart illustrating driving timing of the lightsources 2 a and 2 b and the area sensors 4 a and 4 b. In the figure, “d”represents a light emission duration of the light sources 2 a and 2 b,and “T” represents an imaging period for two dimensional images by thearea sensors 4 a and 4 b. In the surface defect detection processingaccording to the first example, the light sources 2 a and 2 b aredistinguished from each other, by the light sources 2 a and 2 b servingas flash light sources and these flash light sources being caused torepeatedly emit light such that their light emission timings do notoverlap each other.

That is, as illustrated in FIG. 3, in this example, first, the functiongenerator 3 transmits a trigger signal to the light source 2 a and thearea sensor 4 a, the light source 2 a emits the illumination light beamL, and the area sensor 4 a completes capturing of a two-dimensionalimage within the duration d. After completion of the capturing of thetwo-dimensional image by the area sensor 4 a, the function generator 3transmits a trigger signal to the light source 2 b and the area sensor 4b, and a two-dimensional image is captured similarly. According to thisexample, two dimensional images by the individual reflected light beamsfor the illumination light beams L emitted from the respective lightsources are able to be captured with the time difference d and withoutreduction in light quantity.

If conveyance speed of the steel pipe P is fast, the light emissionduration d of the flash light sources is desirably short. This isbecause, the shorter the light emission duration d is; the smaller theshutter delay between the two two-dimensional images obtained by thearea sensors 4 a and 4 b becomes, and thus the smaller the positionaldisplacement between the two-dimensional images due to the shutter delayis able to be made. Further, when detection of a surface defect by useof a subtraction image between the two-dimensional images by theindividual reflected light beams is aimed, the light emission duration dof the flash light sources needs to satisfy a condition expressed bynumerical expression (1):

Light emission duration d[sec]≤Minimum resolution [mm/pixel]×Allowablepositional displacement [pixels]/Line conveyance speed [mm/sec]  (1).

If, a size of a surface defect aimed to be detected is, for example, 20mm, since empirically, signals of at least 5×5 pixels are needed todetect the surface defect, the resolution may be 4 mm/pixel. Further, inthis case, the allowable positional displacement due to the irradiationtimings of the illumination light beams L empirically needs to be notmore than 0.2 pixel, and thus if the conveyance speed of the steel pipeP is 1, 3, or 5 m/s, the light emission duration of the light sources 2a and 2 b needs to be not greater than 800, 270, or 160 μsec,respectively. If the conveyance speed and conveyance direction of thesteel pipe P is constant, this positional displacement may be correctedafter capturing the two-dimensional images.

In this mode, after executing image processing such as calibration,shading correction, noise removal and the like by use of cameraparameters derived in advance for two-dimensional images input from thearea sensors 4 a and 4 b, the image processing device 5 detects asurface defect in an examination target part, by executing subtractionprocessing between the two-dimensional images.

Specifically, if a luminance value of each pixel constituting atwo-dimensional image Ia obtained when the illumination light beam L isemitted from the light source 2 a is Ia(x, y) (where the number ofpixels is X×Y, the x-coordinate is 1≤x≤X, and the y-coordinate is 1≤y≤Y)and a luminance value of each pixel constituting a two-dimensional imageIb obtained when the illumination light beam L is emitted from the lightsource 2 b is Ib(x, y), a luminance value I_diff(x, y) of each pixel oftheir subtraction image I_diff is expressed by numerical equation (2):

I_diff(x, y)=Ia(x,y)−Ib(x,y)  (2).

Examples of the two-dimensional images Ia and Ib capturing a surfacedefect, and scale and a harmless pattern, which are not defects, andtheir subtraction image I_diff are illustrated in FIG. 4(a), (b), and(c), respectively. As illustrated in FIG. 4(a), (b), and (c), in a soundportion, since an angle formed between the normal vector and the lightsource 2 a equals an angle formed between the normal vector and thelight source 2 b despite the scale and the harmless pattern, theluminance value Ia(x, y)=the luminance value Ib(x, y), that is, theluminance value I_diff(x, y)=0. However, in a surface defect portion,since the surface has a concavo-convex shape, a site where the angleformed between the normal vector and the light source 2 a does not equalthe angle formed between the normal vector and the light source 2 b isalways present, and thus the luminance value Ia(x, y)≠the luminancevalue Ib(x, y), that is, the luminance value I_diff(x, y)≠0.

Therefore, by a subtraction device 11 generating a subtraction imagebetween two two-dimensional images, scale and a harmless pattern, whichare not defects, are removed, and only a surface defect is able to bedetected. Only a surface defect is detected as described above, finalevaluation of whether or not the surface defect is harmful is madethrough various feature amounts, and a result of the evaluation isdisplayed on the monitor 6.

If there is a positional displacement between the two two-dimensionalimages and this influences the subtraction image, a two-dimensional lowpass filter is desirably used to reduce the influence of the positionaldisplacement between the two-dimensional images. In this case, if thetwo-dimensional low pass filter is “H,” a luminance value I′_diff(x, y)of the subtraction image is expressed by numerical equation (3):

I′_diff (x,y)=H*(Ia(x,y)−Ib(x,y))  (3).

Further, preferably, as the light sources 2 a and 2 b, light sourcesthat are the same are used, each of the light sources emits light sothat the light becomes uniform parallel light as much as possible, andthe examination target part is approximately planar. However, inapplication to when the surface is a little nonuniform or to a smoothcurved surface like the steel pipe P, a surface defect is able to bedetected by general shading correction.

Further, the angle of incidence of the illumination light beams L isdesirably in a range preventing a mirror reflection component fromentering reflected light from a sound portion and enabling sufficientlight quantity to be secured. We conducted an experiment to investigatethe relationship between angle of incidence of the illumination lightbeams L and reflectivity of a sound portion (base steel portion). Aconfiguration of an apparatus used in the experiment is illustrated inFIG. 5. As illustrated in FIG. 5, in this experiment, light quantityreceived by a power meter 12 when the power meter 12 was fixed to aposition right above a slab sample 14 and angle of incidence θ of alaser 13 was changed from 0° to 90° was measured. Results of theexperiment are illustrated in FIG. 6. As illustrated in FIG. 6, when theangle of incidence θ is in a range of 0° to 20°, the light quantityreceived by the power meter 12 is large due to inclusion of a mirrorreflection component, but when the angle of incidence θ becomes notsmaller than 60°, the light quantity received by the power meter 12 islargely reduced. Therefore, the angle of incidence of the illuminationlight beams L is desirably in a range of 25° to 55° with respect to anormal vector of an examination target part.

Depth direction resolution of an examination target part depends on aninclination angle of a defect and resolutions of the area sensors 4 aand 4 b. The inclination angle of a defect is an angle obtained byorthographically projecting “a normal vector of a defect portion” to “aplane formed of a light source direction vector and a normal vector of asurface of a sound portion of an examination target part,” the angleformed between the orthographically projected vector and the normalvector of the surface of the sound portion. Although dependent oncharacteristics of the surface of the examination target part, whenirradiation is performed with incident light at an angle of incidenceof, for example, 45°, if the inclination angle of the defect is notsmaller than about 10° with respect to the light source direction, ithas been confirmed that a defect signal is detectable by subtractionprocessing. Therefore, if a resolution of one pixel is assumed to be 0.5mm, theoretically, a depth direction resolution of about 0.5×tan10°=0.09 mm is obtained.

Second Example

Next, by referring to FIG. 7, surface defect detection processingaccording to the second example will be described.

In the surface defect detection processing according to a secondexample, by using light sources having wavelength regions notoverlapping each other as the light sources 2 a and 2 b, the lightsources 2 a and 2 b are distinguished from each other. Specifically, asillustrated in FIG. 7, two types of wavelength selection filters 20 aand 20 b having wavelength regions not overlapping each other arearranged at the light sources 2 a and 2 b, and wavelength regions of theillumination light beams L are selected. Further, wavelength selectionfilters 21 a and 21 b having the same wavelength selectioncharacteristics are arranged at the area sensors 4 a and 4 b.

According to this configuration, the reflected light beam of theillumination light beam L from the light source 2 a is received only bythe area sensor 4 a through the wavelength selection filters 20 a and 21a, and the reflected light beam of the illumination light beam L fromthe light source 2 b is received only by the area sensor 4 b through thewavelength selection filters 20 b and 21 b. Therefore, by matchingimaging timings of the area sensors 4 a and 4 b to each other,two-dimensional images by the reflected light beams of the illuminationlight beams L from the light sources 2 a and 2 b are able to be capturedwithout any positional displacement. Processing after capturing thetwo-dimensional images is similar to that of the first example.

When the moving speed of an examination target part is large, to preventpositional displacement due to the movement of the examination targetpart, by using flash light sources as the light sources 2 a and 2 b,imaging times of the two dimensional images may be shortened withoutchanging irradiation timings of the light sources 2 a and 2 b. Further,a configuration may be adopted, in which, by capturing two-dimensionalimages by using a blue transmission filter as the wavelength selectionfilter 20 a and a green transmission filter as the wavelength selectionfilter 20 b and using a single color camera, only the reflected lightbeam of the illumination light beam L from the light source 2 a isreceived in the blue channel and only the reflected light beam of theillumination light beam L from the light source 2 b is received in thegreen channel.

Third Example

Next, by referring to FIG. 8, surface defect detection processingaccording to a third example will be described.

In the surface defect detection processing according to the thirdexample, by using light sources having linear polarizationcharacteristics orthogonal to each other as the light sources 2 a and 2b, the light sources 2 a and 2 b are distinguished from each other.Specifically, as illustrated in FIG. 8, linear polarization plates 30 aand 30 b are arranged at α° and (α+90)° (where α is any angle) at thelight sources 2 a and 2 b, and only light of polarization componentsorthogonal to each other is transmitted therethrough, respectively. Alinear polarization plate means a filter that transmits only a linearpolarization component of a certain direction, with respect to incidentlight. Further, linear polarization plates 31 a and 31 b having the samelinear polarization characteristics as the linear polarization plates 30a and 30 b are arranged at α° and (α+90)° at the area sensors 4 a and 4b.

According to this configuration, the reflected light beam of theillumination light beam L from the light source 2 a is received only bythe area sensor 4 a, and the reflected light beam of the illuminationlight beam L from the light source 2 b is received only by the areasensor 4 b. Therefore, by matching imaging timings of the area sensors 4a and 4 b to each other, two-dimensional images by the reflected lightbeams of the illumination light beams L from the respective lightsources are able to be captured without any positional displacement.

When the moving speed of an examination target part is large, by usingflash light sources as the light sources 2 a and 2 b, imaging times ofthe two dimensional images may be shortened without changing irradiationtimings of the light sources 2 a and 2 b. Positioning and processingafter the capturing of the two dimensional images are similar to thoseof the first and second modes.

Example

In this example, as illustrated in FIG. 9, a surface defect of the steelpipe P was detected by use of a method of using flash light sources asthe light sources 2 a and 2 b and changing light emission timings of thelight sources 2 a and 2 b. Two-dimensional images were captured byarranging the area sensors 4 a and 4 b in a line, and positioning wasperformed by image processing. Results of the surface defect detectionare illustrated in FIG. 10. FIG. 10(a) is a two-dimensional image uponirradiation with the illumination light beam L from the light source 2a, FIG. 10(b) is a two-dimensional image upon irradiation with theillumination light beam L from the light source 2 b, and FIG. 10(c) is asubtraction image between the two-dimensional image illustrated in FIG.10(a) and the two-dimensional image illustrated in FIG. 10(b). S/Nratios of the images illustrated in FIG. 10(a) to (c) were respectively3.5, 3.5, and 6.0, and the SN ratio of the subtraction image improved ascompared when the illumination light beam L was simply emitted from asingle direction.

FIG. 11 is a diagram illustrating results of surface defect detectionprocessing with respect to a portion of the steel pipe, the portionwhere scale has been generated. FIG. 11(a) is a two-dimensional imageupon irradiation with the illumination light beam L from the lightsource 2 a, FIG. 11(b) is a two-dimensional image upon irradiation withthe illumination light beam L from the light source 2 b, and FIG. 11(c)is a subtraction image between the two-dimensional image illustrated inFIG. 11(a) and the two-dimensional image illustrated in FIG. 11(b).Black spots spread across the whole two-dimensional images illustratedin FIG. 11(a) and (b) are the scale, which causes noise. Since the scaleis flat shaped, by the obtainment of the subtraction image, the image ofthe scale was removed. Further, in the subtraction image, as comparedwith the case where the illumination light beam was simply emitted froma single direction, a signal of the scale, which causes noise, wasreduced to about ¼.

First Modified Example

FIG. 12 is a schematic diagram illustrating a configuration of amodified example of the surface defect detecting apparatus according tothe first structure. As illustrated in FIG. 12, in this modifiedexample, illumination light emitted from the single light source 2 a isdivided by plural mirrors 40 a, 40 b, 40 c, and 40 d, and an examinationtarget part of a steel pipe P1 is finally irradiated with theillumination light beams from two directions. In this case, byarrangement of the wavelength selection filters 20 a and 20 b and thelinear polarization plates 30 a and 30 b on the respective optical pathsof the illumination light beams, effects similar to those of the secondand third structures are able to be obtained. Although the illuminationlight beams are emitted from two directions in this modified example,the same applies to when illumination light beams are emitted from notless than three directions.

Second Modified Example

FIG. 13 is a schematic diagram illustrating a configuration of anothermodified example of the surface defect detecting apparatus according tothe first structure. As illustrated in FIG. 13, in this modifiedexample, instead of limiting wavelength of light sources by use of thewavelength selection filters 20 a and 20 b in the surface defectdetecting apparatus illustrated in FIG. 7, wavelength of light sourcesis limited by use of pulse lasers 51 and 51 b and diffusion plates 50 aand 50 b. In this modified example, the light sources are distinguishedfrom each other by irradiation of an examination target part with laserlight beams from the two pulse lasers 51 a and 51 b having wavelengthregions different from each other, from left and right directions. Thediffusion plates 50 a and 50 b are inserted in optical paths of thelaser light beams for irradiation of the entire area of the examinationtarget part with the laser light beams emitted from the pulse lasers 51a and 51 b. Although the illumination light beams are emitted from twodirections in this modified example, the same applies to whenillumination light beams are emitted from not less than threedirections.

Third Modified Example

In this modified example, a dichroic mirror is used instead of thewavelength selection filters 21 a and 21 b arranged at the area sensors4 a and 4 b in the surface defect detecting apparatus illustrated inFIG. 7. The dichroic mirror is a mirror that reflects light of aspecific wavelength component and transmits light of other wavelengthcomponents. By use of the dichroic mirror, wavelength selection filtersbecome unnecessary. Although the illumination light beams are emittedfrom two directions in this modified example, the same applies to a casewhere illumination light beams are emitted from not less than threedirections.

Second Structure

Next, by referring to FIG. 14A to FIG. 22, a configuration and operationof a surface defect detecting apparatus according to the secondstructure will be described. Since the configuration of the surfacedefect detecting apparatus according to this structure is the same asthe configuration of the surface defect detecting apparatus according tothe above described first structure, hereinafter, description of theconfiguration will be omitted, and only the operation of the surfacedefect detecting apparatus will be described.

By executing surface defect detection processing described below, thesurface defect detecting apparatus 1 according to the second structuredistinguishes a concavo-convex surface defect from scale or a harmlesspattern in an examination target part. Scale or a harmless pattern meansa portion having a surface film or surface characteristics with opticalproperties different from those of a base steel portion of a thicknessof about several μm to several tens of μm, and is a portion that becomesa cause of noise in the surface defect detection processing.

Surface Defect Detection Processing

In surface defect detection processing according to one of thestructures after executing image processing such as calibration, shadingcorrection, noise removal, and the like by use of camera parametersderived in advance for two two-dimensional images input from the areasensors 4 a and 4 b, the image processing device 5 generates asubtraction image by executing subtraction processing between thetwo-dimensional images, and detects, from the generated subtractionimage, a concavo-convex surface defect in an examination target part.

Specifically, if a luminance value of each pixel constituting atwo-dimensional image Ia obtained when the illumination light beam L isemitted from the light source 2 a is Ia(x, y) (where the number ofpixels is X×Y, the x-coordinate is 1≤x≤X, and the y-coordinate is 1≤y≤Y)and a luminance value of each pixel constituting a two-dimensional imageIb obtained when the illumination light beam L is emitted from the lightsource 2 b is Ib(x, y), a luminance value I_diff(x, y) of each pixel oftheir subtraction image I_diff obtained by subtraction processing isexpressed by numerical expression (1) already mentioned.

As illustrated in FIG. 4, in a sound portion, regardless of presence orabsence of scale or a harmless pattern, since the angle formed betweenthe normal vector of the surface and the light source 2 a equals theangle formed between the normal vector of the surface and the lightsource 2 b, the luminance value Ia(x, y)=the luminance value Ib(x, y),that is, the luminance value I_diff(x, y)=0. However, in aconcavo-convex surface defect portion, since the surface has aconcavo-convex shape, a site where the angle formed between the normalvector of the surface and the light source 2 a does not equal the angleformed between the normal vector of the surface and the light source 2 bis always present, and thus the luminance value Ia(x, y)≠the luminancevalue Ib(x, y), that is, the luminance value I_diff(x, y)≠0. Therefore,by the subtraction device 11 generating the subtraction image I_diffbetween the two two-dimensional images, an image of scale or a harmlesspattern, which is sound and not a surface defect, is able to be removed.

Next, logic of detecting a concavo-convex surface defect from thesubtraction image I_diff will be described. FIGS. 14A and B are diagramsrespectively illustrating shade and shadow when an examination targetpart is irradiated with the illumination light beam from one of thelight sources when a surface shape of the examination target part isconcave shaped and convex shaped. As illustrated in FIG. 14A, when thesurface shape of the examination target part is concave shaped, the sidenear the light source becomes dark due to reduction in light quantity ofirradiation light per unit area, and the side far from the light sourcebecomes bright due to the approach to a normal reflection direction. Incontrast, as illustrated in FIG. 14B, when the surface shape of theexamination target part is convex shaped, the side near the light sourcebecomes bright due to the approach to a normal reflection direction andthe side far from the light source becomes dark due to a shadow of theconvex shape.

In other words, brightness patterns of reflected light beams of theillumination light beams are different between when the surface shape ofthe examination target part is concave shaped and when the surface shapeis convex shaped. Therefore, by recognition of the brightness pattern ofthe reflected light beam, presence or absence of a concavo-convexsurface defect is able to be detected. Thus, hereinafter, a method ofdetecting a concavo-convex surface defect by recognizing a brightnesspattern of a reflected light beam will be described. Hereinafter, aconcave shaped surface defect will be detected, of concavo-convexsurface defects, but a convex shaped surface defect may be detectedaccording to similar logic. Further, a bright portion mentioned belowmeans a blob having an area not smaller than a predetermined valueobtained by execution of connection processing with respect to pixelshaving luminance not smaller than a predetermined threshold in thesubtraction image I_diff. Further, a dark portion mentioned below refersto a blob, which has an area not smaller than a predetermined valueobtained by execution of connection processing with respect to pixelshaving luminance not greater than a predetermined threshold in thesubtraction image I_diff. A blob means a collection of labelled pixels.

In this structure, a brightness pattern is recognized by extraction of abright portion and a dark portion through execution of thresholdprocessing. Specifically, in the surface defect detecting apparatus 1according to this structure, since the light sources 2 a and 2 b arearranged to be left-right symmetrical to each other about a normalvector of an examination target part, a brightness pattern of reflectedlight resulting from a concavo-convex shape of the surface is generatedin a left-right direction. Left and right of brightness is reversedaccording to the order of subtraction processing, and thus, herein, whenthe right is bright and the left is dark, the surface is concave shapedand when the right is dark and the left is bright, the surface is convexshaped. Therefore, the subtraction image I_diff of the convex shapedsurface defect becomes like the one illustrated in FIG. 15. When imagesof the bright portion and dark portion are binarized respectively withluminance thresholds The and −The, binarized images I_blight and I_darkof the bright portion and dark portion are respectively expressed bynumerical expressions (4):

I_blight(x,y)=1(When I_diff (x, y)≥The)

I_blight(x,y)=0(When I_diff (x, y)<The)

I_dark(x,y)=1(When I_diff (x, y)≤−The)

I_dark(x,y)=0(When I_diff (x, y)>−The)

After binarizing the images of the bright portion and dark portion asdescribed above and, as necessary, executing connection and isolatedpoint removal, by calculating a positional relation between the brightportion and dark portion, presence or absence of a concavo-convexsurface defect is detected. There are various methods of calculating thepositional relation between the bright portion and dark portion and,hereinafter, three representative calculation methods will be described,but any other method enabling calculation of the positional relationbetween the bright portion and dark portion may be adopted.

A first positional relation calculation method is a method ofcalculating the positional relation between the bright portion and darkportion by execution of expansion and contraction processing in aspecific direction with respect to the bright portion and dark portion.A flow chart of this calculation method is illustrated in FIG. 16. Inthis method, since a concave shaped surface defect is detected, a case,where a brightness pattern with the right bright and the left dark isrecognized, will be described. The right being bright and the left beingdark mean that there is always the dark portion on the left side of thebright portion and there is always the bright portion on the right sideof the dark portion. In this calculation method, first, the imageprocessing device 5 executes expansion processing in the right directionwith respect to the dark portion and executes expansion processing inthe left direction with respect to the bright portion (Steps S1 a and S1b). When images of the bright portion and dark portion that have beensubjected to the expansion processing are respectively denoted asI_blight_extend and I_dark_extend, and the expanded length is W, theexpansion processing is expressed by numerical equations (5). With thetop left of the two-dimensional image being the origin, the downwarddirection is positive along a y-axis direction and the rightwarddirection is positive along an x-axis direction.

I_blight_extend(xl,y)=1 x−W≤xl≤x(When I_blight(x,y)=1)

I_dark_extend(xl,y)=1 x≤xl≤x+W(When I_dark(x,y)=1)  (5)

In this method, although the bright portion and dark portion areexpanded by the same length W, the expanded length W is not necessarilythe same, and to be extreme, expansion processing may be executed withrespect to only one of the bright portion and dark portion. Further, theexpanded length W also depends on the size of the surface defect desiredto be detected.

Next, by executing AND processing with respect to the imagesI_blight_extend and I_dark_extend of the bright portion and dark portionthat have been subjected to the expansion processing as expressed bynumerical equation (6), the image processing device 5 extracts a defectcandidate portion image I_defect, which is an overlapping portionbetween the images I_blight_extend and I_dark_extend of the brightportion and dark portion that have been subjected to the expansionprocessing (Steps S2 a and S2 b).

I_defect=I_blight_extend & I_dark_extend  (6)

Next, after executing connection and isolated point removal processingas necessary with respect to each defect candidate portion imageI_defect obtained, the image processing device 5 generates a defectcandidate blob I_defect_blob by executing labeling processing (Step S3).The image processing device 5 extracts a feature amount of each defectcandidate blob I_defect_blob, and determines, based on a result of theextraction, whether or not each defect candidate blob I_defect_blob is aconcave shaped surface defect (Steps S4 a and S4 b). Investigating thefeature amount of the defect candidate blob I_defect_blob requiresinformation of the bright portion and dark portion, and thus the brightportion and dark portion are restored from the defect candidate blobI_defect_blob.

Specifically, since a bright portion is always present on the right sideof a defect candidate portion and a dark portion is always present onthe left side thereof, the image processing device 5 searches the darkportion binarized image I_dark to the left with the center of gravity ofthe defect candidate blob I_defect_blob being a starting point, andregards a blob that is found first as a dark portion defect candidateblob I_dark_blob. Similarly, the image processing device 5 searches thebright portion binarized image I_blight to the right with the center ofgravity of the defect candidate blob I_defect_blob being a startingpoint, and regards a blob found first as a bright portion defectcandidate blob I_blight_blob. The image processing device 5 extractsfeature amounts from the bright portion defect candidate blobI_blight_blob and dark portion defect candidate blob that have beenrestored as described above, and determines, based on the extractedfeature amounts, whether or not each defect candidate blob I_defect_blobis a concave shaped surface defect. Specific feature amounts differaccording to defects and thus without mentioning the specific featureamounts herein, an example thereof will be described in a laterdescribed example.

In a second positional relation calculation method, after the abovedescribed threshold processing is executed and as necessary, connectionand isolated point removal processing is executed; a bright portion anda dark portion are extracted, labeling is executed, and a positionalrelation between the bright portion and the dark portion is recognized,to thereby detect a concave shaped surface defect. Specifically,firstly, the image processing device 5 recognizes a bright portion and adark portion individually by labeling, and obtains center of gravityinformation of the bright portion and dark portion. Next, the imageprocessing device 5 determines, from the center of gravity informationof the bright portion and dark portion, whether or not the center ofgravity of the dark portion is present in a predetermined range on aright side of each bright portion. If the center of gravity of the darkportion is present therein, the image processing device 5 recognizes thecombination of the bright portion and dark portion forming a pair as abrightness pattern, and determines whether or not it is a concave shapedsurface defect, by executing feature mount analysis of the brightnesspattern. Although the brightness pattern is recognized by use of thecenter of gravity information herein, information used in therecognition of the brightness pattern is not necessarily the center ofgravity information as long as the information enables positions of thebright portion and dark portion to be grasped (for example, their upperend positions, lower end positions, and the like).

In a third positional relation calculation method, without executing theabove described threshold processing, by recognizing a brightnesspattern by use of a filter, a concave shaped surface defect is detected.Specifically, in the surface defect detecting apparatus 1 illustrated inFIG. 1, since the light sources 2 a and 2 b are arranged left-rightsymmetrically about a normal line of an examination target part, abrightness pattern caused by concavity and convexity of a surfacethereof is generated in the left-right direction. FIGS. 17A and B arediagrams respectively illustrating an example of a subtraction image,and a one-dimensional profile of a brightness pattern on a line segmentL4 illustrated in FIG. 17A.

As illustrated in FIGS. 17A and B, for a concave shaped surface defect,the right is bright and the left is dark, and thus the one-dimensionalprofile of the brightness pattern becomes a characteristicone-dimensional profile, in which the right side is mountain shaped andthe left side is valley shaped. Thus, in this structure, a filter H withthe right side being mountain shaped and the left side being valleyshaped is generated in advance, and by subjecting the subtraction imageI_diff to the filter H as expressed by numerical equation (7), atwo-dimensional image I_cont with reduced high frequency noise and withonly the brightness pattern emphasized is generated.

I_cont=H*I_diff  (7)

FIGS. 18A and B are diagrams respectively illustrating a two-dimensionalimage of the filter H generated in advance, and an example of aone-dimensional profile thereof in the left-right direction. FIGS. 19Aand B are diagrams respectively illustrating a subtraction image thathas been subjected to filtering using the filter H illustrated in FIGS.18A and B, and a one-dimensional profile thereof in the left-rightdirection. As illustrated in FIGS. 19A and B, a two-dimensional imagewith reduced high frequency noise and with only the brightness patternthereof emphasized is obtained.

As necessary, several types of filters having different ranges in awidth direction may be prepared in advance to be compatible with manysurface defect sizes. After executing connection and isolated pointremoval processing as necessary, with respect to the two-dimensionalimage with its brightness pattern emphasized as described above, theimage processing device 5 extracts the defect candidate portion imageI_defect by executing threshold processing. The image processing device5 detects a concave shaped surface defect by executing processingsimilar to that of the first positional relation calculation method,with respect to the extracted defect candidate portion image I_defect.

As clarified from the above description, in the surface defect detectionprocessing according to one of the structures, the same examinationtarget part is irradiated with the illumination light beams L atapproximately the same angle of incidence from different directions byuse of the two distinguishable light sources 2 a and 2 b, the images bythe reflected light beams of the respective illumination light beams Lare obtained, the bright portion and dark portion of the image obtainedby execution of subtraction processing between the obtained images areextracted, and presence or absence of a concavo-convex surface defect isdetermined from the positional relation between the extracted brightportion and dark portion and the irradiation directions of theillumination light beams L, and thus a concavo-convex surface defect isable to be accurately distinguished from scale or a harmless pattern.

In this structure, although the left and right brightness pattern isrecognized since the light sources are arranged left-rightsymmetrically, even if the arrangement positions of the light sourcesare not left and right, and are not up-down symmetrical or notsymmetrical, a concavo-convex surface defect is able to be detected bysimilar processing. Specifically, when the light sources are arranged tobe up-down symmetrical to each other, since the brightness pattern justchanges from the left-right direction to the up-down direction, if thebrightness pattern is rotated by 90 degrees, a concavo-convex surfacedefect is able to be detected by similar processing.

Further, as illustrated in FIG. 20, when the light sources 2 a and 2 bare arranged such that irradiation directions of the illumination lightbeams differ from each other by 90 degrees, if the surface defect isconcave shaped, the side near the light sources becomes dark and theside far from the light sources becomes bright, and if the surfacedefect is convex shaped, the side near the light sources becomes brightand the side far from the light sources becomes dark. Specifically, ifthe surface defect is concave shaped, a two-dimensional image obtainedby the illumination light beam from the light source 2 a is asillustrated in FIG. 21A, and a two-dimensional image obtained by theillumination light beam from the light source 2 b is as illustrated inFIG. 21B. Therefore, the subtraction image has a brightness pattern witha contrast from the lower left to the upper right, as illustrated inFIG. 21C. Thus, if the brightness pattern is rotated by 45 degrees, by amethod similar to that for the left-right direction brightness pattern,a concave shaped surface defect is able to be detected. Further, sincesubtraction images of plural patterns are able to be respectivelyobtained by use of three or more light sources, accuracy of surfacedefect detection is able to be improved even more.

Further, in this structure, although a concavo-convex surface defect isdetected for when the illumination light beams are emitted from thedirections symmetrical about the normal line of the examination targetpart, the irradiation directions of the illumination light beams are notnecessarily symmetrical. Furthermore, the surface defect detectionprocessing according to this structure is applicable to manufacturinglines in general for steel materials regardless of whether they are hotor cold.

Example

In this example, surface defect detection processing using the abovedescribed first positional relation calculation method was applied to anexamination target part, where a pit defect had been formed and to asound examination target part, where a pit defect had not been formed.In this example, as feature amounts, a luminance ratio, an area ratio,and circularities of a bright portion and a dark portion werecalculated. The circularities are values obtained by division of areasof the bright portion and dark portion by squares of lengths of theircircumferences and normalization, and are used in determining whether ornot shapes of the bright portion and dark portion are close to acircular shape. If the cause is the same among surface defects,luminances and areas are not likely to be significantly different fromone another in the left and right signals, and accuracy of surfacedefect detection is improved by evaluating the left-right balance by useof the luminance ratio and area ratio. Further, since shade and shadoware evaluated, the bright portion and dark portion hardly becomecircular shaped, and since those close to a circular shape are able tobe determined to be due to a different cause, circularities wereincluded in the feature amounts. Further, areas of the bright portionand dark portion were calculated, and only any surface defect with anarea not smaller than a predetermined value was made detectable. Resultsof the detection are illustrated in FIG. 22. As illustrated in FIG. 22,according to this structure, a pit defect, and a sound portion, where apit defect is not formed, were confirmed to be accuratelydistinguishable from each other.

Third Structure

Next, by referring to FIG. 23 to FIG. 26, a configuration and operationof a surface defect detecting apparatus according to the third structurewill be described. Since the configuration of the surface defectdetecting apparatus according to this structure is the same as theconfigurations of the surface defect detecting apparatuses according tothe above described first and second structures, hereinafter,description of the configuration will be omitted, and only the operationof the surface defect detecting apparatus will be described.

By executing surface defect detection processing described below, thesurface defect detecting apparatus 1 according to the third structuredistinguishes a concavo-convex surface defect from scale or a harmlesspattern in an examination target part. Scale or a harmless pattern meansa portion having a surface film or surface characteristics with opticalproperties different from those of a base steel portion of a thicknessof about several um to several tens of μm, and is a portion that becomesa cause of noise in the surface defect detection processing.

Surface Defect Detection Processing

The surface defect detecting apparatus 1 according to the abovedescribed second structure detects a concavo-convex surface defect byrecognizing a brightness pattern of reflected light. However, dependingon the shape or position of a surface defect, the brightness pattern ofthe reflected light may be unable to be generated. Specifically,particularly when the normal vector direction at the surface of thesteel pipe is largely different from the optical axis direction of thearea sensor and the shape of the surface defect is elongated asillustrated in FIG. 23, one of the bright portion and dark portion ishidden from the field of view and only the other one of the brightportion and dark portion is detected, and thus the brightness pattern ofthe reflected light may be unable to be generated.

Accordingly, separately from the logic of detecting a concavo-convexsurface defect by the recognition of a brightness pattern of reflectedlight, the surface defect detection processing according to one of themethods has logic of detecting an elongated defect by recognition of ashape of a surface defect. An elongated defect mentioned herein means asurface defect having a linear elongated shape characteristic. FIG. 24is a flow chart illustrating a flow of detection processing for anelongated defect according to an example of our methods. In this method,a surface defect to be detected is a concave shaped elongated defect,but a convex shaped elongated defect may also be detected by thisdetection processing if only the other one of the bright portion anddark portion is detected.

In the surface defect detection processing according to one of themethods, first, after binarizing a subtraction image between a brightportion and a dark portion with a predetermined luminance threshold, andas necessary, executing connection and isolated point removal, the imageprocessing device 5 executes labeling processing on images of the brightportion and dark portion (Steps S1 a and S1 b). Next, the imageprocessing device 5 extracts images of a bright portion and a darkportion having areas not smaller than a predetermined threshold, fromthe labeling processed images of the bright portion and dark portion(Step S2). The image processing device 5 then calculates a shape featureamount of a surface defect, which becomes an index of elongatedness, forthe extracted images of the bright portion and dark portion, anddetects, based on the calculated shape feature amount of the surfacedefect, an elongated defect (Step S3).

Examples of shape feature amounts of a surface defect, the shape featureamounts becoming indices of elongatedness, include a major axis-minoraxis ratio of an ellipse, a maximum Feret's diameter, a circularity, anda convex polygon filling rate. Specifically, if a major axis-minor axisratio is calculated as a shape feature amount, as illustrated in FIG.25A, first, the image processing device 5 fits an ellipse R to an imageof a bright portion or dark portion. Methods of fitting an ellipse to animage include the least squares method, the secondary moment derivationmethod and the like, but in consideration of the calculation time, thesecondary moment derivation method is more useful. The image processingdevice 5 calculates lengths of a major axis L1 and a minor axis L2 ofthe fitted ellipse R, and obtains a ratio between the calculated majoraxis L1 and minor axis L2 as a shape feature amount.

A Feret's diameter is, as illustrated in FIG. 25B, a length L3 of a mapobtained when an image of a bright portion or dark portion isorthographically projected one-dimensionally. If a maximum Feret'sdiameter is calculated as a shape feature amount, firstly, the imageprocessing device 5 calculates, as the maximum Feret's diameter, themaximum value of the length of the orthographic projection whilerotating the image of the bright portion or dark portion by 180 degrees.The image processing device 5 then finds, as a shape feature amount, aratio between a Feret's diameter in a direction orthogonal to a site,for which the maximum Feret's diameter has been calculated, and themaximum Feret's diameter.

Further, as illustrated in FIG. 25C, a circularity means a valuenormalized such that the closer the shape of the bright portion or darkportion is to a circle, the closer to 1 a value obtained by dividing anarea of the bright portion or dark portion by a square of a length of acircumference of the bright portion or dark portion becomes.Furthermore, a convex polygon filling rate means an area rate of abright portion or dark portion with respect to an area of a polygoncircumscribing the bright portion or dark portion, and the more linearthe bright portion or dark portion is, the more closer to 1 the valuethereof becomes. Therefore, if the circularity of the bright portion ordark portion is low, and the convex polygon filling rate is high on thecontrary, the shape of that bright portion or dark portion is able to bedetermined to be elongated shaped.

When an elongated defect is detected, by considering, not only a shapefeature amount of the surface defect, but also a direction of thesurface defect such as a vertical direction, a horizontal direction, ora diagonal direction, accuracy of detection for the elongated defect isable to be improved. For example, a direction of a surface defect isable to be checked by finding: a direction in which the major axis isoriented if the major axis-minor axis ratio is calculated as a shapefeature amount of a surface defect; and a rotation angle of the image ofthe bright portion or dark portion upon obtainment of the maximumFeret's diameter if the maximum Feret's diameter is calculated as ashape feature amount of the surface defect. Further, although detailsthereof will be omitted, by subjecting the image to a linear filteremphasizing a specific direction, a direction of a surface defect mayalso be checked.

Further, in this structure, the light sources are arranged left-rightsymmetrically about the normal vector of the steel pipe, but even if thearrangement positions of the light sources are not left-rightsymmetrical about the normal vector of the steel pipe, and is notup-down symmetrical or not symmetrical as illustrated in FIG. 20, forexample, an elongated defect is able to be detected by similar detectionprocessing. Furthermore, while scale or a harmless pattern is flat andthus even if the incident direction of the illumination light beamchanges, the scale or the harmless pattern looks the same; when theincident light beam of the illumination light beam changes, an elongateddefect looks differently, and thus the elongated defect is able to bedetected by the above described logic. Moreover, since subtractionimages of plural patterns are able to be obtained respectively by use ofthree or more light sources, accuracy of detection for an elongateddefect is able to be improved further.

As clarified from the above description, in the surface defect detectionprocessing according to one of the structures, the same examinationtarget part is irradiated with the illumination light beams L atapproximately the same angle of incidence from different directions byuse of the two distinguishable light sources 2 a and 2 b, the images bythe reflected light beams of the respective illumination light beams Lare obtained, the bright portion and dark portion of the image obtainedby execution of subtraction processing between the obtained images areextracted, the shape feature amount that becomes an index ofelongatedness of the extracted bright portion and dark portion iscalculated, and presence or absence of an elongated defect is determinedbased on the calculated shape feature amount, and thus the elongateddefect is able to be accurately distinguished from scale or a harmlesspattern.

Example

In this example, our surface defect detection processing was applied toan examination target part, where an overrun defect had been formed, andto a sound examination target part, where an overrun defect had not beenformed. An overrun defect is a surface defect characterized in that thesurface defect has a linear elongated shape, and is directed obliquelyupward to the right with respect to the rolling direction. Presence orabsence of an overrun defect was determined by calculating a majoraxis-minor axis ratio and a major axis angle as shape feature amounts ofa surface defect and comparing the calculated major axis-minor axisratio and major axis angle with predetermined thresholds. Results of thedetermination are illustrated in FIG. 26. As illustrated in FIG. 26,according the surface defect detection processing of this method, anoverrun defect and a sound portion, where an overrun defect is notformed, were confirmed to be accurately distinguishable from each other.

The structure methods, to which the contents of disclosure has beenapplied, have been described above, but the disclosure is not limited bythe description and drawings forming a part of disclosure through thesestructures, methods and examples. That is, any other structures, workingexamples, operation techniques, and the like implemented by thoseskilled in the art or the like based on the structures and methods areall included in the scope of this disclosure and the appended claims.

INDUSTRIAL APPLICABILITY

A surface defect detecting method and a surface defect detectingapparatus that enable a surface defect to be accurately distinguishedfrom scale or a harmless pattern, are provided.

1. A detecting method of optically detecting a surface defect of amoving steel material, the method comprising: an irradiation step ofirradiating an examination target part with illumination light beamsfrom different directions with two or more distinguishable light sourceswhose light emission durations are set based on at least an allowablepositional displacement of an image, the two or more distinguishablelight sources repeatedly emitting light such that their light emissiontimings thereof do not overlap each other; and a detection step ofobtaining images by reflected light beams of the respective illuminationlight beams and detecting a surface defect in the examination targetpart by executing subtraction processing between the obtained images. 2.The method according to claim 1, wherein the light emission durationsare set based on the allowable positional displacement of the image,minimum resolution of the image and a moving speed of the steelmaterial.
 3. The method according to claim 1, wherein the light emissiondurations, the allowable positional displacement of the image, minimumresolution of the image and a moving speed of the steel material satisfya condition expressed by expression (1):Light emission duration d[sec]≤Minimum resolution [mm/pixel]×Allowablepositional displacement [pixels]/Line conveyance speed [mm/sec].  (1) 4.The method according to claim 1, wherein the obtained images byreflected light beams of the respective illumination light beams areobtained using plural imaging devices whose optical axes are adjusted tobe coaxial with one another.
 5. The method according to claim 1, whereinthe detection step includes a step of obtaining images by reflectedlight beams of the respective illumination light beams by separating thereflected light beams of the respective illumination light beams thathave been mixed with one another by using filters that transmit lightbeams having wavelengths the same as wavelengths of the illuminationlight beams.
 6. The method according to claim 4, wherein the detectionstep includes a step of adjusting, by using any of a half mirror, a beamsplitter, and a prism, optical axes of the plural imaging devices, whichobtain images by reflected light beams of the respective illuminationlight beams, to be coaxial with one another.
 7. A surface defectdetecting apparatus that optically detects a surface defect of a movingsteel material, the surface defect detecting apparatus comprising: anirradiation unit configured to irradiate an examination target part withillumination light beams from different directions with two or moredistinguishable light sources whose light emission durations are setbased on at least an allowable positional displacement of an image, thetwo or more distinguishable light sources repeatedly emit light suchthat their light emission timings do not overlap each other; and adetection unit configured to obtain images by reflected light beams ofthe respective illumination light beams and detect a surface defect inthe examination target part by executing subtraction processing betweenthe obtained images.